Machine Learning Tutorial
Selected Reading
- Machine Learning - Discussion
- Machine Learning - Useful Resources
- Machine Learning - Quick Guide
- Machine Learning - Conclusion
- Machine Learning - Implementing
- Machine Learning - Skills
- Machine Learning - Deep Learning
- Artificial Neural Networks
- Machine Learning - Unsupervised
- Machine Learning - Scikit-learn Algorithm
- Machine Learning - Supervised
- Machine Learning - Categories
- What is Machine Learning?
- Machine Learning - Traditional AI
- What Today’s AI Can Do?
- Machine Learning - Introduction
- Machine Learning - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
What Today’s AI Can Do?
Machine Learning - What Today’s AI Can Do?
When you tag a face in a Facebook photo, it is AI that is running behind the scenes and identifying faces in a picture. Face tagging is now omnipresent in several apppcations that display pictures with human faces. Why just human faces? There are several apppcations that detect objects such as cats, dogs, bottles, cars, etc. We have autonomous cars running on our roads that detect objects in real time to steer the car. When you travel, you use Google Directions to learn the real-time traffic situations and follow the best path suggested by Google at that point of time. This is yet another implementation of object detection technique in real time.
Let us consider the example of Google Translate apppcation that we typically use while visiting foreign countries. Google’s onpne translator app on your mobile helps you communicate with the local people speaking a language that is foreign to you.
There are several apppcations of AI that we use practically today. In fact, each one of us use AI in many parts of our pves, even without our knowledge. Today’s AI can perform extremely complex jobs with a great accuracy and speed. Let us discuss an example of complex task to understand what capabipties are expected in an AI apppcation that you would be developing today for your cpents.
Example
We all use Google Directions during our trip anywhere in the city for a daily commute or even for inter-city travels. Google Directions apppcation suggests the fastest path to our destination at that time instance. When we follow this path, we have observed that Google is almost 100% right in its suggestions and we save our valuable time on the trip.
You can imagine the complexity involved in developing this kind of apppcation considering that there are multiple paths to your destination and the apppcation has to judge the traffic situation in every possible path to give you a travel time estimate for each such path. Besides, consider the fact that Google Directions covers the entire globe. Undoubtedly, lots of AI and Machine Learning techniques are in-use under the hoods of such apppcations.
Considering the continuous demand for the development of such apppcations, you will now appreciate why there is a sudden demand for IT professionals with AI skills.
In our next chapter, we will learn what it takes to develop AI programs.
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